
import html

from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends


if is_bsa_available():
		import bsa
		from bsa import BeautifulSoup


lowercase    :   Dict						=			logging.get_logger(__name__)




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def __init__(   self						:List[str]	,  **a						:Optional[int]		)						->					Optional[int]:
								requires_backends(self	,  ["bs4"]		)
								super().__init__(**a		)







	def   _lowerCamelCase							(   self						:Optional[int]	,  a						:int		)						->					Tuple:
								__UpperCamelCase      :  Tuple       =   []
								__UpperCamelCase      :  Dict       =   []
								__UpperCamelCase      :  List[str]       =   element if element.name else element.parent
								for parent in child.parents:  # type: bs4.element.Tag
															__UpperCamelCase      :  Dict       =   parent.find_all(child.name	,  recursive=a		)
															xpath_tags.append(child.name		)
															xpath_subscripts.append(
															    0 if 1 == len(a		) else next(i for i, s in enumerate(a	,  1		) if s is child		)		)
															__UpperCamelCase      :  Optional[Any]       =   parent
								xpath_tags.reverse()
								xpath_subscripts.reverse()
								return xpath_tags, xpath_subscripts







	def   _lowerCamelCase							(   self						:int	,  a						:Tuple		)						->					int:
								__UpperCamelCase      :  Dict       =   BeautifulSoup(a	,  "html.parser"		)

								__UpperCamelCase      :  Dict       =   []
								__UpperCamelCase      :  List[str]       =   []
								__UpperCamelCase      :  Dict       =   []

								for element in html_code.descendants:
															if type(a		) == bsa.element.NavigableString:
																						if type(element.parent		) != bsa.element.Tag:
																													continue

																						__UpperCamelCase      :  Optional[Any]       =   html.unescape(a		).strip()
																						if not text_in_this_tag:
																													continue

																						all_doc_strings.append(a		)

																						__UpperCamelCase  ,		__UpperCamelCase      :  str       =   self.xpath_soup(a		)
																						stringaxtag_seq.append(a		)
																						stringaxsubs_seq.append(a		)

								if len(a		) != len(a		):
															raise ValueError("Number of doc strings and xtags does not correspond"		)
								if len(a		) != len(a		):
															raise ValueError("Number of doc strings and xsubs does not correspond"		)

								return all_doc_strings, stringaxtag_seq, stringaxsubs_seq







	def   _lowerCamelCase							(   self						:str	,  a						:Tuple	,  a						:Any		)						->					str:
								__UpperCamelCase      :  Tuple       =   ""
								for tagname, subs in zip(a	,  a		):
															xpath += f'/{tagname}'
															if subs != 0:
																						xpath += f'[{subs}]'
								return xpath







	def __call__(   self						:List[str]	,  a						:Any		)						->					BatchFeature:
								__UpperCamelCase      :  Any       =   False

								# Check that strings has a valid type
								if isinstance(a	,  a		):
															__UpperCamelCase      :  str       =   True
								elif isinstance(a	,  (list, tuple)		):
															if len(a		) == 0 or isinstance(html_strings[0]	,  a		):
																						__UpperCamelCase      :  Dict       =   True

								if not valid_strings:
															raise ValueError(
															    "HTML strings must of type `str`, `List[str]` (batch of examples), "
															    f'but is of type {type(a		)}.'		)

								__UpperCamelCase      :  List[str]       =   bool(isinstance(a	,  (list, tuple)		) and (isinstance(html_strings[0]	,  a		))		)

								if not is_batched:
															__UpperCamelCase      :  Dict       =   [html_strings]

								# Get nodes + xpaths
								__UpperCamelCase      :  Union[str, Any]       =   []
								__UpperCamelCase      :  int       =   []
								for html_string in html_strings:
															__UpperCamelCase  ,		__UpperCamelCase  ,		__UpperCamelCase      :  Any       =   self.get_three_from_single(a		)
															nodes.append(a		)
															__UpperCamelCase      :  str       =   []
															for node, tag_list, sub_list in zip(a	,  a	,  a		):
																						__UpperCamelCase      :  Any       =   self.construct_xpath(a	,  a		)
																						xpath_strings.append(a		)
															xpaths.append(a		)

								# return as Dict
								__UpperCamelCase      :  Optional[Any]       =   {"nodes": nodes, "xpaths": xpaths}
								__UpperCamelCase      :  List[str]       =   BatchFeature(data=a	,  tensor_type=a		)

								return encoded_inputs

from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
		from ..models.auto import AutoTokenizer




class 					lowerCamelCase__				:




	'''simple docstring'''




	def   _lowerCamelCase							(   self						:Optional[Any]	,  a						:int		)						->					Any:
								raise NotImplementedError()







	def   _lowerCamelCase							(   self						:Any		)						->					Optional[int]:
								raise NotImplementedError()




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def __init__(   self						:List[Any]	,  a						:"AutoTokenizer"	,  a						:bool = False	,  **a						:Tuple		)						->					Union[str, Any]:
								__UpperCamelCase      :  int       =   tokenizer
								__UpperCamelCase      :  Any       =   skip_prompt
								__UpperCamelCase      :  Union[str, Any]       =   decode_kwargs

								# variables used in the streaming process
								__UpperCamelCase      :  Union[str, Any]       =   []
								__UpperCamelCase      :  str       =   0
								__UpperCamelCase      :  str       =   True







	def   _lowerCamelCase							(   self						:List[str]	,  a						:Union[str, Any]		)						->					Any:
								if len(value.shape		) > 1 and value.shape[0] > 1:
															raise ValueError("TextStreamer only supports batch size 1"		)
								elif len(value.shape		) > 1:
															__UpperCamelCase      :  Optional[int]       =   value[0]

								if self.skip_prompt and self.next_tokens_are_prompt:
															__UpperCamelCase      :  Optional[Any]       =   False
															return

								# Add the new token to the cache and decodes the entire thing.
								self.token_cache.extend(value.tolist()		)
								__UpperCamelCase      :  Optional[int]       =   self.tokenizer.decode(self.token_cache	,  **self.decode_kwargs		)

								# After the symbol for a new line, we flush the cache.
								if text.endswith("\n"		):
															__UpperCamelCase      :  Optional[int]       =   text[self.print_len :]
															__UpperCamelCase      :  Dict       =   []
															__UpperCamelCase      :  int       =   0
								# If the last token is a CJK character, we print the characters.
								elif len(a		) > 0 and self._is_chinese_char(ord(text[-1]		)		):
															__UpperCamelCase      :  Optional[int]       =   text[self.print_len :]
															self.print_len += len(a		)
								# Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
								# which may change with the subsequent token -- there are probably smarter ways to do this!)
								else:
															__UpperCamelCase      :  Any       =   text[self.print_len : text.rfind(" "		) + 1]
															self.print_len += len(a		)

								self.on_finalized_text(a		)







	def   _lowerCamelCase							(   self						:List[str]		)						->					List[str]:
								# Flush the cache, if it exists
								if len(self.token_cache		) > 0:
															__UpperCamelCase      :  str       =   self.tokenizer.decode(self.token_cache	,  **self.decode_kwargs		)
															__UpperCamelCase      :  str       =   text[self.print_len :]
															__UpperCamelCase      :  str       =   []
															__UpperCamelCase      :  int       =   0
								else:
															__UpperCamelCase      :  int       =   ""

								__UpperCamelCase      :  Optional[Any]       =   True
								self.on_finalized_text(a	,  stream_end=a		)







	def   _lowerCamelCase							(   self						:Union[str, Any]	,  a						:str	,  a						:bool = False		)						->					str:
								print(a	,  flush=a	,  end="" if not stream_end else None		)







	def   _lowerCamelCase							(   self						:Optional[int]	,  a						:Optional[Any]		)						->					str:
								# This defines a "chinese character" as anything in the CJK Unicode block:
								#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
								#
								# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
								# despite its name. The modern Korean Hangul alphabet is a different block,
								# as is Japanese Hiragana and Katakana. Those alphabets are used to write
								# space-separated words, so they are not treated specially and handled
								# like the all of the other languages.
								if (
								    (cp >= 0x4e_00 and cp <= 0x9f_ff)
								    or (cp >= 0x34_00 and cp <= 0x4d_bf)  #
								    or (cp >= 0x2_00_00 and cp <= 0x2_a6_df)  #
								    or (cp >= 0x2_a7_00 and cp <= 0x2_b7_3f)  #
								    or (cp >= 0x2_b7_40 and cp <= 0x2_b8_1f)  #
								    or (cp >= 0x2_b8_20 and cp <= 0x2_ce_af)  #
								    or (cp >= 0xf9_00 and cp <= 0xfa_ff)
								    or (cp >= 0x2_f8_00 and cp <= 0x2_fa_1f)  #
								):  #
															return True

								return False




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def __init__(   self						:Any	,  a						:"AutoTokenizer"	,  a						:bool = False	,  a						:Optional[float] = None	,  **a						:Dict		)						->					str:
								super().__init__(a	,  a	,  **a		)
								__UpperCamelCase      :  str       =   Queue()
								__UpperCamelCase      :  Dict       =   None
								__UpperCamelCase      :  Optional[int]       =   timeout







	def   _lowerCamelCase							(   self						:List[Any]	,  a						:str	,  a						:bool = False		)						->					Dict:
								self.text_queue.put(a	,  timeout=self.timeout		)
								if stream_end:
															self.text_queue.put(self.stop_signal	,  timeout=self.timeout		)







	def __iter__(   self						:Tuple		)						->					Tuple:
								return self







	def   _lowerCamelCase							(   self						:List[Any]		)						->					Dict:
								__UpperCamelCase      :  List[Any]       =   self.text_queue.get(timeout=self.timeout		)
								if value == self.stop_signal:
															raise StopIteration()
								else:
															return value